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 Duration 21 hours

Course Outline

Fundamentals of Oracle Data Warehousing

  • Data warehouse architecture and practical applications
  • Differentiating between OLTP and OLAP workloads
  • Essential elements of an Oracle DW solution

Designing Warehouse Schemas

  • Dimensional modeling approaches: star and snowflake structures
  • Utilization of fact and dimension tables
  • Managing slowly changing dimensions (SCD)

Data Ingestion and ETL Methodologies

  • Designing ETL workflows leveraging SQL and PL/SQL
  • Employing external tables and SQL*Loader utilities
  • Implementing incremental loads and Change Data Capture (CDC)

Partitioning Strategies and Performance Enhancement

  • Partitioning techniques: range, list, and hash
  • Query pruning mechanisms and parallel processing
  • Partition-wise joins and recommended best practices

Compression Techniques and Storage Efficiency

  • Hybrid columnar compression methods
  • Strategies for data archival
  • Balancing storage optimization for both performance and cost-effectiveness

Advanced Querying and Analytical Capabilities

  • Utilizing materialized views and automatic query rewriting
  • Advanced analytical SQL functions (RANK, LAG, ROLLUP)
  • Temporal analysis and real-time reporting generation

Surveillance and Tuning of the Data Warehouse

  • Tracking and evaluating query performance
  • Managing resource allocation and workload distribution
  • Indexing methodologies specific to warehousing environments

Concluding Remarks and Future Directions

Requirements

  • A solid grasp of SQL principles and core Oracle database concepts
  • Prior experience interacting with Oracle 12c/19c in either an administrative or development capacity
  • Foundational understanding of data warehousing principles

Target Audience

  • Data warehouse developers
  • Database administrators
  • Business intelligence specialists

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